Almost every retailer has recognized the need to track the purchases made by customers in order to understand the desires and trends of its customers. Generally, such information is stored in one or more computerized databases. These databases are able to track purchases made throughout a retail chain, and can be broken down according to a variety of parameters, such as by product, region, store, or department. Once the database of purchases has been created, it can be used for forecasting, inventory management, and for promotional planning.
Many retailers have understood that these types of databases can be even more useful if they are able to track the habits of individual customers. If this can be done accurately, it would be possible to improve forecasting and to perform complex demographic research on their customers. In addition, customer specific purchase information would allow the retailer to greatly improve the efficiency of its marketing and promotional planning, and would even allow direct one-on-one marketing according to a customer's individual tastes, as determined by the customer's previous purchases and general buying habits.
Unfortunately, it can be difficult to properly associate a particular purchase at a retailer with a particular customer. Some means must be employed to identify the customer at the point of sale. For instance, a store representative may ask the customer for their phone number. This information is then entered into a device at the point of sale, and then compared with the existing database of customers. The comparison determines whether the customer already exists in the database. If an entry for that customer does exist in the database, the purchase then being made is added to the database entry for an existing customer. Otherwise, a new customer entry is added to the database.
Various methods can be used to identify customers at the point of sale, with each method creating a different degree of confidence that the customer has been successfully identified. The most accurate method may be to request identifying information such as a phone number directly from the customer. This information can then be compared with the database. If similar or identical information is retrieved, the customer will be requested to verify that the information in the database is accurate. If the match in the database is for a different individual, a new record in the database is created for that individual. Sometimes, multiple entries in the database might match the information received from the customer. In these circumstances, the customer can be directly asked to select the appropriate entry, and, if necessary, multiple entries in the database for the same individual can be merged together.
Unfortunately, requesting such detailed, identifying information from the customer at the point of sale has several negative effects. First, the customer is often annoyed at the perceived invasion into their privacy. Second, requesting such information slows down the sale transaction, which decreases the efficiency for the store and increases customer frustration with any delay. Finally, customers may choose to provide inaccurate information to indicate their displeasure at the system, which has obvious implications to the usefulness of the database.
As a result, several companies have provided a service to retailers that identify a customer according to the credit card number used by the customer at the point of sale. The system simply looks the number up in a reverse listing of identities and credit card numbers provided by credit card issuers. Using this system, all credit card purchases can be associated with a particular individual, without any of the adverse consequences described above. In addition, because each credit card number is uniquely assigned to one individual or household, the returned identifying information has a high degree of accuracy.
Unfortunately, recent statutory changes in the United States has made the provision of identifying information from credit card numbers difficult. As a result, retailers are now searching for a way to automatically identify customers at the point of sale without requiring the customer to directly identify themselves.